本課程將帶領同學學習機率學的基本理論及其應用，主要內涵包括：認識機率空間的定義，了解並複習離散型分佈的相關概念，學習連續型分佈、多變數分佈與變數轉換、以及中央極限定理等相關理論及其應用。This course will lead students to learn the basic theories and applications of probability learning. The main connotations include: understanding the definition of probability space, understanding and replicating the related concepts of dispersed distribution, learning theorems and applications of continuous distribution, multivariate distribution and variable conversion, as well as the central extreme theorem.
機率學主要的目的在於介紹和解析機會的結構及其相關之變數與函
數。
這方面的知識為許多進一步研究涉不確定性因素問題的學問的
基礎。本課程引導同學接觸一些有趣的理論和實例。
The main purpose of opportunity learning is to introduce and analyze the structure of opportunities and their related variables and functions.
Number.
This knowledge is a study of many further research on the problems of uncertain factors.
Basic. This course guides students to come across some interesting theories and examples.
Hogg, R.V.and E.A. Tanis and D.L.Zimmerman : Probability and Statistical Inference (9th edition).
Hogg, R.V. and E.A. Tanis and D.L.Zimmerman : Probability and Statistical Inference (9th edition).
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 兩次小考兩次小考 Two small exams |
30 | 每次各佔學期總成績15% |
| 期中考期中考 Midterm exam |
25 | |
| 期末考期末考 Final exam |
25 | |
| 平時成績平時成績 Regular achievements |
20 | 包含小小考、出席狀況及課堂表現等等。 |
